{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b5a252ef-ac0b-4208-ad74-e317ad3855b2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-11T08:52:05.099370Z",
     "iopub.status.busy": "2022-06-11T08:52:05.098795Z",
     "iopub.status.idle": "2022-06-11T08:52:05.612455Z",
     "shell.execute_reply": "2022-06-11T08:52:05.611843Z",
     "shell.execute_reply.started": "2022-06-11T08:52:05.099315Z"
    }
   },
   "outputs": [],
   "source": [
    "# 导入包\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c031262d-b2fb-42f8-8c23-fa05ba09a966",
   "metadata": {},
   "source": [
    "### 三种方式：\n",
    "1. 使用plot函数绘图时，传入Line2D属性值，设置样式\n",
    "2. 使用plot返回的Line2D对象，单独设置样式，set_Line2D属性名()\n",
    "3. 使用plt.setp一次性批量设置样式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c4c375fb-b267-4599-9c1b-13cfede3b314",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-11T08:53:53.577837Z",
     "iopub.status.busy": "2022-06-11T08:53:53.577453Z",
     "iopub.status.idle": "2022-06-11T08:53:53.590022Z",
     "shell.execute_reply": "2022-06-11T08:53:53.589356Z",
     "shell.execute_reply.started": "2022-06-11T08:53:53.577812Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[13, 14, 12, 5, 10, 12, 3, 12, 14, 2]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 创建y轴数据\n",
    "yData=[np.random.randint(2,15) for x in range(10)]\n",
    "yData"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f88b67e3-761e-4ed0-8417-5e0cc51a6fa9",
   "metadata": {},
   "source": [
    "## 一、通过plot函数设置样式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "c49e3ee5-d0d9-45d0-845b-9171e692c9c1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-11T09:22:39.455001Z",
     "iopub.status.busy": "2022-06-11T09:22:39.454653Z",
     "iopub.status.idle": "2022-06-11T09:22:39.566995Z",
     "shell.execute_reply": "2022-06-11T09:22:39.566176Z",
     "shell.execute_reply.started": "2022-06-11T09:22:39.454975Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1866a22f0>]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制\n",
    "# 样式：\n",
    "# 1. 节点+虚线\n",
    "# 2. **kwargs:(Line2D属性，查官网matplotlib.lines.Line2D)\n",
    "#   1. linewidth\n",
    "#   2. color\n",
    "plt.plot(yData,\"H--\",linewidth=3,color=\"b\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be5b2796-4d15-4acf-8c82-e963531ba08c",
   "metadata": {},
   "source": [
    "## 二、通过Line2D对象设置样式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "74fc47ef-0fdb-4107-9396-587f2dec84bb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-11T09:17:35.968045Z",
     "iopub.status.busy": "2022-06-11T09:17:35.967728Z",
     "iopub.status.idle": "2022-06-11T09:17:35.974544Z",
     "shell.execute_reply": "2022-06-11T09:17:35.973726Z",
     "shell.execute_reply.started": "2022-06-11T09:17:35.968021Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[4, 6, 10, 10, 7, 6, 10, 4, 12, 6]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 创建数据\n",
    "yData1=[np.random.randint(2,15) for x in range(10)]\n",
    "yData1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "99e2f70d-5245-477e-bd9e-191f91e5664b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-11T09:17:40.413977Z",
     "iopub.status.busy": "2022-06-11T09:17:40.413280Z",
     "iopub.status.idle": "2022-06-11T09:17:40.419813Z",
     "shell.execute_reply": "2022-06-11T09:17:40.419090Z",
     "shell.execute_reply.started": "2022-06-11T09:17:40.413946Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[13, 14, 8, 12, 9, 13, 8, 13, 14, 2]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 创建数据\n",
    "yData2=[np.random.randint(2,15) for x in range(10)]\n",
    "yData2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "efa68880-6c44-46a2-a71a-7030d6550e31",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-11T09:22:22.085496Z",
     "iopub.status.busy": "2022-06-11T09:22:22.085138Z",
     "iopub.status.idle": "2022-06-11T09:22:22.194653Z",
     "shell.execute_reply": "2022-06-11T09:22:22.193786Z",
     "shell.execute_reply.started": "2022-06-11T09:22:22.085471Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot函数会返回一组Line2D对象列表\n",
    "# 列表中每个元素对应一条线\n",
    "# 设置折线图绘制\n",
    "lines = plt.plot(np.arange(10),yData1,np.arange(10),yData2)\n",
    "# 设置第0个Line2D对象的颜色\n",
    "lines[0].set_color(\"k\")\n",
    "# 设置第0个Line2D对象的线宽\n",
    "lines[0].set_linewidth(4)\n",
    "# 设置第1个Line2D对象的颜色\n",
    "lines[1].set_color(\"r\")\n",
    "# 设置第1个Line2D对象的样式\n",
    "lines[1].set_linestyle(\"-.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bbb34402-870b-4518-85d2-f13929971e33",
   "metadata": {
    "tags": []
   },
   "source": [
    "## 三、通过plt.setp来设置样式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "6cdbe31b-98bd-4f28-b3c0-4da0f1f7fbc4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-06-11T09:25:05.609866Z",
     "iopub.status.busy": "2022-06-11T09:25:05.609194Z",
     "iopub.status.idle": "2022-06-11T09:25:05.722201Z",
     "shell.execute_reply": "2022-06-11T09:25:05.721298Z",
     "shell.execute_reply.started": "2022-06-11T09:25:05.609839Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[None, None]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘图之后动态修改（用得比较少）\n",
    "lines = plt.plot(np.arange(10),yData1,np.arange(10),yData2)\n",
    "plt.setp(lines, linewidth=4)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
